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Data Science Articles & Videos

The Purpose of Platforms in Data ScienceLittle has been written about scaling an organization of data scientists and the organizational support necessary to do data science well, at scale. I’ve spent the past year at Uber working on exactly this question, and almost 5 years working on data science at Uber generally, and I wanted to share some of my learnings on the power of platforms when it comes to data science...

Solving 4x4 KenKen Puzzles with Computer VisionI wanted to do something that was challenging but not beyond my skills for a first project. As I was browsing college websites for ideas I found a blog post which described the process of solving Sudoku puzzles with computer vision. It seemed a bit too easy and seemed to have been done by many in the past so I wanted to do something more difficult and original. I resolved to solve KenKen puzzles instead...

This is how I used machine learning to predict Villanova would win the 2016 March Madness TournamentMy machine learning model accurately predicted Villanova would win the championship, netted me first place out of 34 in my office pool, 63rd place out of 608 in the Kaggle competition (top 11%) and ~123,000 out of 13 million in ESPN’s overall leaderboard (top 1%). I wrote a post about this before the tournament with the promise that if it worked out, I’d do a full writeup and release the code. I’m thankful to say it all panned out and here we go!...

Statistics for SoftwareSoftware development begins as a quest for capability, doing what could not be done before. Once that what is achieved, the engineer is left with the how. In enterprise software, the most frequently asked questions are, “How fast?” and more importantly, “How reliable?”. Questions about software performance cannot be answered, or even appropriately articulated, without statistics...

Data Normalization in PythonIn this post we'll be digging into some MLB payroll data. In particular I'm going to show you how you can use normalization techniques to compare seemlingly incomparable data! Sounds like magic? Well it's actually really simple, but I think these little Python scripts will really help you out :)...

Jobs

The Content Science & Algorithms team is a world class group of data scientists focusing on the super interesting question of which movies and shows Netflix should create or purchase the rights to. The team seeks to use data science to better understand this problem and build tools to support the content acquisition teams in their decision making. We are looking for experienced individuals who are passionate about data science and enjoy working in a collaborative environment. Members of the team typically work on one or two projects (e.g. predicting movie viewership) over any six month period...